Cyber criminals utilize the phishing tactic to seem to be reputable websites in order to collect personal data. The unique light weight phishing detection method presented is entirely based on the URL (uniform resource location). The SVM (support vector machine) evaluated record of phishing URLs, generates a fairly satisfactory recognition rate. Numerous books in the literature addressed the phishing assault. However, because to their complicated computation and high energy consumption, those systems are not the best for smartphones and other embedded devices. Just six URL features are needed OTP by the Suggested algorithm to complete the recognition. The features that are specified include the size of the URL, the number of dots, hyphens, and numeric characters, along with a corresponding discrete variable to the IP address contained in the URL, and lastly, the similarity index. The similarity index, a feature we present for the first time as input to the phishing detection systems, enhances the overall prediction rate, as demonstrated by the study's result.
Keywords: Fake Review Products, Detections, cyber security, community computing, cybercrime.